Triple

T23394574
Position Surface form Disambiguated ID Type / Status
Subject Urs Hölzle E559318 entity
Predicate name P16 FINISHED
Object Urs Hölzle NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Urs Hölzle | Statement: [Urs Hölzle, name, Urs Hölzle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urs Hölzle
Context triple: [Urs Hölzle, name, Urs Hölzle]
  • A. Urs Hölzle chosen
    Urs Hölzle is a Swiss computer scientist best known as one of Google’s first employees and its longtime Senior Vice President of Technical Infrastructure, where he has shaped the company’s large-scale computing systems.
  • B. Eric Schmidt
    Eric Schmidt is an American technologist and businessman best known as the former CEO and executive chairman of Google (later Alphabet Inc.), where he helped oversee the company’s rapid global expansion and innovation.
  • C. Diane Greene
    Diane Greene is a prominent American technology executive and entrepreneur best known as a co-founder and former CEO of VMware and a former CEO of Google Cloud.
  • D. Sergey Brin
    Sergey Brin is a computer scientist and internet entrepreneur best known as the co-founder of Google.
  • E. John Doerr
    John Doerr is a prominent American venture capitalist and early investor in major technology companies such as Google and Amazon.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e24549610c8190a069d6411ce5f661 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a49eb3b881909da7f1c47c67c81f completed April 29, 2026, 6:26 a.m.
Created at: April 17, 2026, 5:36 p.m.